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cake

Documentation Release Rust Report CI License

Cake is a multimodal AI inference server written in Rust that can run models as a single node, or shard them across a heterogeneous cluster of devices — iOS, Android, macOS, Linux, Windows — to run workloads that wouldn't fit on a single GPU, effectively leveraging planned obsolescence to make AI more accessible and democratic.

This is experimental code that's being actively developed and changed very quickly.

Key Features

  • Multi Modal — Text generation, image generation (Stable Diffusion, FLUX), and voice synthesis (VibeVoice TTS with voice cloning).
  • Multi Model — 15 text model families, 6 image model variants, and 2 TTS models. Architecture auto-detected from HuggingFace checkpoints.
  • Multi Platform — CUDA, Metal, Vulkan, and CPU backends across Linux, macOS, Windows, iOS, and Android.
  • Multi Node — Shard transformer blocks across devices with zero-config mDNS clustering or manual topology. Also runs entirely on a single machine.
  • OpenAI-Compatible API — REST API with streaming, plus a built-in web UI and TUI chat client.
  • Docker — Container builds for Linux/NVIDIA with docker-compose cluster support.

Quick Start

Build

cargo build --release --features cuda        # Linux (NVIDIA)
cargo build --release --features metal       # macOS (Apple Silicon GPU)
cargo build --release --features accelerate  # macOS (Apple Silicon CPU, F32 models)
cargo build --release --features vulkan      # Linux (AMD/Intel/Steam Deck)
cargo build --release                        # CPU only (portable)

Models

Download models from HuggingFace with cake pull. Models are stored in the standard HuggingFace cache directory (~/.cache/huggingface/hub/) and are shared with any other tools that use the same cache (transformers, huggingface-cli, etc.).

cake pull evilsocket/Qwen3-0.6B             # text model (600M params)
cake pull evilsocket/flux1-dev               # image model (FLUX.1-dev FP8)
cake pull evilsocket/VibeVoice-1.5B          # voice synthesis model

cake list                                    # show all locally available models
cake rm evilsocket/Qwen3-0.6B               # delete a cached model

Models are also downloaded automatically on first use if not already cached.

Single Node

Run any model locally on a single machine — architecture is auto-detected from the model's config.json:

# Text generation
cake run evilsocket/Qwen3-0.6B "Explain quantum computing in simple terms"

# Interactive TUI chat
cake chat Qwen/Qwen3-0.6B

# Start an API server + web UI
cake serve evilsocket/Qwen3-0.6B

# Image generation (FLUX.1-dev FP8)
cake run evilsocket/flux1-dev --model-type image-model --image-model-arch flux1 \
  "a cyberpunk cityscape at night"

# Voice synthesis with voice cloning
cake run evilsocket/VibeVoice-1.5B --model-type audio-model \
  --voice-prompt voice.wav "Hello world"

Distributed

Shard a model across multiple machines using --cluster-key. Workers don't need the model data — the master automatically streams the required tensor weights over the network (compressed with zstd, verified with CRC32 checksums). Workers cache received data locally for subsequent runs.

# Start workers on any machines (no model needed)
cake run --cluster-key mysecret --name gpu-server-1    # machine A
cake run --cluster-key mysecret --name macbook          # machine B

# Run inference from the master (has the model)
cake run evilsocket/Qwen3-0.6B "Hello" --cluster-key mysecret

# Or start an API server as the master
cake serve evilsocket/Qwen3-0.6B --cluster-key mysecret

The master discovers workers via mDNS, assigns layers proportionally to each device's VRAM/compute, and pushes only the required weight shards. See the clustering documentation for manual topology files and advanced configuration.

For the full usage guide and API reference, check the project documentation.

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License

Released under the FAIR License (Free for Attribution and Individual Rights) v1.0.0.

  • Non-commercial use (personal, educational, research, non-profit) is freely permitted under the terms of the license.
  • Commercial use (SaaS, paid apps, any monetization) requires visible attribution to the project and its author. See the license for details.
  • Business use (any use by or on behalf of a business entity) requires a signed commercial agreement with the author. Contact [email protected] for inquiries.

To see the licenses of the project dependencies, install cargo license with cargo install cargo-license and then run cargo license.

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Distributed inference for mobile, desktop and server.

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